Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…This study shows that advanced machine learning models, particularly BNN and NODE, can predict pharmaceutical solubility and improve crystallization process design and optimization.…”
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Secondary throughput maximization scheme for non-linear energy harvesting cognitive radio networks by Haijiang GE, Ning JIA, Kaikai CHI, Yunzhi CHEN

“…Aiming at a cognitive radio network (CRN) consisting of a pair of primary users and M pairs of secondary users, the secondary throughput maximization for CRN based on the non-linear energy harvesting model was studied.Specifically, in the case of considering secondary transmitter (ST) circuit power, the secondary throughput maximization (STM) problem with primary users’ throughput demands was first modeled as a non-linear optimization problem and then transformed into a convex optimization problem.Finally, a low-complexity algorithm combining the golden section and dichotomy was proposed.By applying this low-complexity algorithm, the optimal time allocation of the primary transmitter (PT)’s energy transmission and secondary users’ information transmission, and the optimal transmission power of PT were obtained.In addition, for the case of neglecting the ST circuit power, the convex property of the STM problem was first proved, and then a more efficient algorithm was designed to solve it.The simulation results show that compared with the equal time allocation method and the link gain priority method, the proposed design algorithm significantly improves the throughput of secondary users.…”
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Qualitative modification of geometrically oriented methods for constructing spatial curves in C3D FairCurveModeler by V. G. Mufteev, F. T. Ziganshina, V. I. Gumerov, R. I. Nabiev, G. M. Efimova

“…The article provides a detailed algorithm for improving the C3D FairCurveModeler commands for constructing a class F spatial curve with approximation by a rational cubic spline Bezier curve (NURBzS-curve) and with approximation by a highdegree B-spline curve. …”
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Predictive model for determining the indications for automated 3D ultrasound for screening patients at low risk of developing breast tumors by A. E. Garanina, A. V. Kholin

“…The developed algorithms will help optimize screening and referral for additional examinations, which is of practical importance for improving diagnostics and optimizing healthcare resources.…”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…Finally,the improved dung beetle optimization (IDBO) algorithm is used to optimize the hyper-parameters of the model. …”
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Generative Adversarial and Transformer Network Synergy for Robust Intrusion Detection in IoT Environments by Pardis Sadatian Moghaddam, Ali Vaziri, Sarvenaz Sadat Khatami, Francisco Hernando-Gallego, Diego Martín

“…Additionally, an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm is employed to fine-tune the hyper-parameters of the hybrid model, further enhancing learning stability and detection performance. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…In genomics, ML methods enabled nuanced disease subtype discovery and improved the accuracy of cancer risk assessment and pharmacogenomic modeling. …”
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Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…Existing approaches lack adaptability to evolving terminologies and insufficiently address the complex interaction dynamics inherent in multi-disciplinary frameworks.MethodsTo address these limitations, we propose a Synergistic Collaboration Framework (SCF) integrated with an Adaptive Synergy Optimization Strategy (ASOS). SCF models IPC as a dynamic multi-agent system, where disciplines are represented as intelligent agents interacting within a weighted graph structure. …”
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Balancing line hardening, distributed generation and de-energization for wildfire risk mitigation with microgrid formation by Mengqi Yao, Shunbo Lei, Weimin Wu, Duncan S. Callaway

“…An adopted column-and-constraint generation algorithm is developed to solve the model and obtain the optimal decisions. …”
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A Novel Time Delay Nonsingular Fast Terminal Sliding Mode Control for Robot Manipulators with Input Saturation by Thanh Nguyen Truong, Anh Tuan Vo, Hee-Jun Kang

“…Manipulator systems are increasingly deployed across various industries to perform complex, repetitive, and hazardous tasks, necessitating high-precision control for optimal performance. However, the design of effective control algorithms is challenged by nonlinearities, uncertain dynamics, disturbances, and varying real-world conditions. …”
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Dengue Early Warning System and Outbreak Prediction Tool in Bangladesh Using Interpretable Tree‐Based Machine Learning Model by Md. Siddikur Rahman, Miftahuzzannat Amrin, Md. Abu Bokkor Shiddik

“…The optimal tree‐based ML model with strong interpretability was created by comparing various ML models using the hyperparameter optimization technique. …”
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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

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Power-Yeoh: A Yeoh-Type Hyperelastic Model with Invariant I₂ for Rubber-like Materials by Subraya Krishna Bhat, Keerthan A.

“…In this paper, we improve the Yeoh model, a classical and popular I₁-based hyperelastic model with high versatility. …”
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Research on computer multi feature fusion SVM model based on remote sensing image recognition and low energy system by Yangming Wu, Hao Wu, Xin Tang, Jianwei Lv, Rufei Zhang

“…Aiming at the limitations of the traditional SVM model in processing high-dimensional data, an optimization algorithm is designed to reduce the computational complexity and improve the recognition accuracy of the model through dimensionality reduction and feature selection. …”
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Thermal Error Prediction in High-Power Grinding Motorized Spindles for Computer Numerical Control Machining Based on Data-Driven Methods by Quanhui Wu, Yafeng Li, Zhengfu Lin, Baisong Pan, Dawei Gu, Hailin Luo

“…The subsequent problem of thermal error compensation can be effectively solved by a suitable thermal error model, which is crucial for improving the machining accuracy of the actual machining process. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…This study presents an enhanced deep learning model designed to improve the accuracy and adaptability of recognition algorithms for robotic arm-based harvesting. …”
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Predicting the Traffic Crashes of Taxi Drivers by Applying the Non-Linear Learning of ANFIS-PSO with M5 Model Tree by E. Abbasi, M. Hadji Hosseinlou

“…In order to improve the generalization ability of a single data driving algorithm, a cluster of ANFIS models with different nodes and hidden layers are implemented to extract the inherent relationship between traffic accident rates and human factors. …”
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A deep learning-based hybrid method for PM2.5 prediction in central and western China by Zuhan Liu, Zihai Fang, Yuanhao Hu

“…The model integrates the transformer and LSTM architectures and employs parameter optimization through the particle swarm optimization (PSO) algorithm. …”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
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Multi-cohort study in gastric cancer to develop CT-based radiomic models to predict pathological response to neoadjuvant immunotherapy by Ze-Ning Huang, Hao-Xiang Zhang, Yu-Qin Sun, Xing-Qi Zhang, Yi-Fen Lin, Cai-Ming Weng, Chao-Hui Zheng, Ping-Li, Jia-Bin Wang, Qi-Yue Chen, Long-Long Cao, Mi Lin, Ru-Hong Tu, Chang-Ming Huang, Jian-Xian Lin, Jian-Wei Xie

“…Radiomic features were extracted from CT images, and a multi-step feature selection procedure was applied to identify the top 20 representative features. Nine ML algorithms were implemented to build prediction models, with the optimal algorithm selected for the final prediction model. …”
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